Past Returns Research Articles

Adaptive online mean-variance portfolio selection with transaction costs

Online portfolio selection is attracting increasing attention in both artificial intelligence and finance communities due to its efficiency and practicability in deriving optimal investment strategies in real investment activities where the market information is constantly renewed every second. The key issues in online portfolio selection include predicting the future returns of risky assets accurately given historical data and providing optimal investment strategies for investors in a short time. In the existing online portfolio selection studies, the historical return data of one risky asset is used to estimate its future return. In this paper, we incorporate the peer impact into the return prediction where the predicted return of one risky asset not only depends on its past return data but also the other risky assets in the financial market, which gives a more accurate prediction. An adaptive moving average method with peer impact (AOLPI) is proposed, in which the decaying factors can be adjusted automatically in the investment process. In addition, the adaptive mean-variance (AMV) model is firstly applied in online portfolio selection where the variance is employed to measure the investment risk and the covariance matrix can be linearly updated in the investment process. The adaptive online moving average mean-variance (AOLPIMV) algorithm is designed to provide flexible investment strategies for investors with different risk preferences. Finally, numerical experiments are presented to validate the effectiveness and advantages of AOLPIMV.

Leaving the (fund) gate ajar: Investor protection or marketing ploy?

Using a sample of active equity funds in China, we explore for the first time mutual funds that impose discretionary inflow restrictions (gates) on investors. Contrary to managers' claim, we find no compelling evidence that inflow gates serve to protect investor interests. Despite their superior past performance, inflow-restricted funds exhibit a significant decline in subsequent returns. In addition, funds tilt toward a riskier investment strategy when a gate is in place. Our analyses reveal that partly-closed gates further exacerbate investors' chasing of past returns, attracting extra flows and locking in more retail investors. Overall, we suggest that leaving the fund gate ajar to investors appears to be more of a marketing ploy than a form of investor protection. Our findings carry important implications for mutual fund investors, asset managers, and policy makers alike.

February, share turnover, and momentum in China

We show that significant momentum exists in China equity returns outside the month of February for both the past return and the 52-week high momentum ranking criteria. For 6-month holding periods, the magnitudes range from 73 bp to 110 bp per month in both raw and factor-adjusted returns using the China factors of Liu et al. (2019). A strong seasonal February reversal masks momentum when all months are considered together. The reversal is associated with a spike in turnover for recent loser stocks, which we attribute to an appetite for lottery-like stocks by retail investors in the season of the Chinese New Year. We show that the turnover difference between winner and loser stocks is a significant determinant of momentum in all three culturally Chinese equity markets—China, Taiwan, and Hong Kong. However, consistent with the dominance of retail investors in China, the February seasonal is weaker in Taiwan and non-existent in Hong Kong, and strong enough to mask momentum in other months only in China.

Market momentum amplifies market volatility risk: Evidence from China’s equity market

We examine the role of a belief-based momentum indicator, measured by conditional past returns (CPR), in the realized volatility (RV) predictability of equity markets. Based on the week- and month-horizon CPR, we construct the HAR-CPR and HAR-LCPR models on the basis HAR-RV model. Here, the HAR-LCPR model additionally includes the daily leverage factor in the absence of daily CPR. In China, we find that: 1) week- and month-horizon CPR have significantly positive impacts on one-, five-, and 22-days-ahead RVs; 2) our out-of-sample results further indicate that the HAR-LCPR model performs best in forecasting one- and five-days-ahead RVs, whereas the HAR-CPR model is a more reliable forecasting model for 22-days-ahead volatility; 3) the performance also passes various robustness tests, including sub-period performance testing, alternative training rolling window, and alternative RV estimation. We show the economic mechanism underlying the predictive role of CPR from the perspective of investors’ trading activities.

The forecast ability of a belief-based momentum indicator in full-day, daytime, and nighttime volatilities of Chinese oil futures

China launched its domestic crude oil futures market in 2018 and this nascent market is steadily developing. Studying volatility predictability for Chinese crude oil futures has important academic and practical significance. In this study, we examine the predictive impacts of a novel predictor, the belief-based momentum indicator of conditional past return (CPR), a cluster of predictors from the domestic (Chinese) stock and oil markets and the US stock and options markets, and global finance-related indicators. In addition to the full-day oil realized volatility (ORV), we also forecast the daytime and nighttime ORVs. First, we find that the novel CPR indicator has significant incremental predictive information for the full-day, daytime, and nighttime ORVs, whether in the short, middle, or long term. Furthermore, the CPR indicator is the most reliable among the four endogenous predictors. Second, predictors of the Chinese stock market have no effective predictive information; instead, predictors from the US stock and options market have great impacts on future Chinese ORVs. Third, our evidence shows that the predictability of the night ORV is half that of the daytime ORV, and the VIX is relevant for the nighttime ORV. Our research helps Chinese policymakers improve the crude oil market mechanism and prevent market risks.

Unveiling the relationship between oil and green bonds: Spillover dynamics and implications

This study investigates the spillover dynamics and directionality between oil prices (OP) and green bonds (GB) using a bivariate Generalized Autoregressive Conditional Heteroskedasticity (GARCH) framework. The research aims to contribute to the understanding of the complex relationship between OP and GB and provide valuable policy insights to stakeholders. The results confirm the presence of significant spillovers between the two markets, indicating a transmission of risk and contagion. While the unconditional correlation between the returns of OP and GB is close to zero, bivariate asymmetric GARCH-BEKK estimations reveal a clear connection between the two markets. Past return shocks in the GB market are found to mitigate subsequent volatility in the OP, suggesting a level of substitution between the two markets. Volatility spillovers between the two markets are also evident, although their signs vary. This study contributes to the literature by filling a research gap and offering insights into the spillover dynamics and directionality between OP and GB. The results highlight the interconnectedness and transmission of risk between the two markets, suggesting the need to consider their relationship for investment decisions. Policymakers, investors, and other stakeholders can benefit from the insights provided in this research for effective risk management and investment strategies.

The overlooked momentum traders in 401(k) plans

Using a unique dataset on over one million 401(k) traders, we investigate momentum trading in 401(k) plans. We identify momentum traders in each quarter and evaluate how these traders perform. Results indicate the existence of momentum traders. However, there is no evidence that they successfully improve their portfolio performance. Instead, momentum sellers sell the outperformed funds. Overall, momentum traders could lose up to 2.14% per year. In seeking to explain such losses, we observe that 401(k) momentum traders follow a naïve momentum strategy. They do not have the ability to select funds with momentum investing styles but, instead, simply chase past returns.

Investigating mean reversion in financial markets using Hurst Model

In the dynamic world of financial markets, the prices of assets can exhibit dramatic fluctuations, sometimes soaring to dizzying heights or plummeting to alarming lows. However, amidst the chaos, a fascinating phenomenon emerges: a tendency for prices to revert back to their long-term average or mean level. This concept known as mean reversion has intrigued traders, investors, and researchers for decades. Understanding mean reversion provides valuable insights into market dynamics, investor behavior, and the potential for profitable trading strategies. The aim of this study was to empirically investigate mean reversion in financial markets. This study employed a Hurst model for a sample of five financial markets from June 1, 2018 to June 1, 2023. The findings revealed that four out of the five sampled financial markets exhibit mean reversion, which challenges the efficient market hypothesis concept. Therefore, portfolio managers and active market participants can utilize long-term memory to optimize asset allocation decisions by considering the persistent effects of past returns and adjusting portfolio weights to take advantage of potential return predictability and manage risk.

Market reactions to layoff announcements during crises: Examining impacts and conditioners

There is limited research on the effect of layoff announcements on stock returns during difficult economic conditions. We use event study and cross-sectional analysis to examine the impacts of layoff announcements on stock market returns during recent crises. Findings reveal that layoff announcements significantly negatively impact firm stock returns in both the short and medium terms, with firm leverage, price-to-book ratio, liquidity, return on assets, volatility, and past returns being significant conditioners. Results highlight the reaction of markets to layoff announcements and the importance of considering firm and market characteristics in forecasting the impact of layoff announcements on stock performance.

Channel Effects of Korean Fund Distributors and Affiliates: Focusing on Historical Return-Chasing Phenomenon and Financial Regulations

This study investigates the channel effects of fund distributors, specifically in terms of past return chasing, while also considering whether these fund distributors are affiliated with asset management firms or not. The empirical findings are summarized as follows. First, affiliated funds exhibit about 24% lower past return chasing compared to their non-affiliated counterparts. This result suggests that the criteria employed for selection and management of affiliate funds are notably less stringent in their reliance on past performance compared to non-affiliated funds. Second, the past return chasing behavior of affiliated funds has increased subsequent to the implementation of regulations governing fund distribution for such funds. In other words, the management of return rates for affiliate funds has become more stringent. Third, affiliate funds sold by fund distributors have higher searching costs or higher sales remuneration, particularly evident among small and low-age funds, compared to non-affiliated funds. This indicates that there is a difference in fund attributes depending on the affiliation status. This paper make a substantive contribution by providing empirical evidence on the impact of financial sales regulations, such as restrictions imposed on sales of affiliated funds.

Impacts of climate pact on global oil and gas sector stocks

PurposeThe purpose of this study is to examine the impacts of the Glasgow Climate Pact on global oil and gas sector stocks. Further, this study also examines if the nations' Climate Change Performance Index (CCPI) and World Energy Trilemma Index (WETI) drive the abnormal returns around the event.Design/methodology/approachThe authors apply the event study analysis to 691 global oil and gas firms across 52 countries. Further, they apply the cross-sectional examination of cumulative abnormal returns (CARs) across 502 firms.FindingsThe emerging markets experienced significant negative abnormal returns on the event day. The CCPI negatively affects longer pre-event CARs, while WETI significantly negatively associates with CARs during longer pre- and post-event windows. Volatility is negatively related to pre- and post-event abnormal returns, while past returns positively drive pre-event period CARs but negatively drive post-event window CARs. This study finds an interesting association between liquidity (CACL) and CARs, as CACL positively drives pre-event CARs, but post-event CARs are negatively associated with CACL. The CARs do not significantly correlate with leverage, size and book-to-market ratio.Practical implicationsThis study's findings on the impact of climate risks on financial markets have significant implications for global regulatory bodies. Policymakers should reduce stock volatility and enhance environmental disclosures by publicly traded companies to accurately price and assess the potential impacts of climate risks. Governments should examine the effects of environmental restrictions on investor behavior, especially in developing countries with limited access to capital. Therefore, policymakers need to consider the far-reaching impacts of environmental regulations while introducing them.Originality/valueClimate risks are expected to impact the global financial market significantly. Prior studies provide limited evidence on how such climate pacts impact the oil and gas sector. Hence, this study, while bridging this gap, provides important implications for policymakers and stakeholders, particularly the emerging markets that are more sensitive.

Cryptocurrency Momentum and VIX premium

The cryptocurrency momentum premium, defined as the risk premium exposure to the cryptocurrencies with higher past return, is a key factor in the cryptocurrency market. In this paper, we investigate whether VIX, VIX premium (Cheng, 2019), or economic policy uncertainty (EPU) can predict changes in cryptocurrency momentum premiums. The empirical analysis indicates that higher VIX premiums can increase the one-month-ahead momentum premium, and that VIX and EPU levels are not predictors of momentum premiums. Overall, we demonstrate that uncertainty can affect the cryptocurrency momentum premium through VIX futures rather than VIX itself or news-based information (i.e., EPU).

Did the Indian stock market sail the Russia-Ukraine storm safely?

With a sample of 1422 NSE-listed stocks, this study employs the event study method to find the impact of the Russian invasion of Ukraine 2022 on the Indian stock market. Further, cross-sectional regression captures the firm characteristics capable of driving abnormal returns. While the abnormal returns of the Indian stock markets are significant and negative during the pre-invasion period and on the date of military initiation, they are significantly positive during the post-invasion period except on t + 6. The cross-sectional examination of the cumulative abnormal returns with the firm-specific variables indicates that while size, leverage, and BTM negatively impact the pre-invasion abnormal returns, firm liquidity is insignificant; during the post-event period, the past returns and stock volatility positively impact and can predict the abnormal returns. The study provides important implications for policymakers, firms, banks, and investors in managing their financial structure and making informed investment decisions. The findings can also be applied to other emerging markets, serving as a reference for policymakers and contributing to the broader understanding of firms' behavior during crises.

Time-varying MAX preference: Evidence from revenue announcements

In this study, I examine whether investors' demand for stocks with maximum daily returns (MAX stocks) increases before the firms' revenue announcements. My setting is the Taiwan stock market in which listed firms are uniquely required to declare their previous month's revenues. I find that investors' preference for MAX stocks is stronger prior to revenue announcements, causing high MAX stocks to outperform low MAX stocks in the pre-announcement window. The MAX spread remains significant even after accounting for institutional ownership, past returns, and investor attention. Although the desire for MAX stocks is the main driver behind the higher returns for high MAX stocks before revenue announcements, investor attention amplifies this gambling tendency. Prior to revenue announcements, investors prefer those MAX stocks whose prices are far from their 52-week highs. By contrast, this phenomenon does not exist when stock prices are close to the 52-week high.

Extrapolative beliefs about Bitcoin returns

Using survey data from Sentix which records whether investors are bullish, bearish, or neutral about the future price of Bitcoin, we examine how investors form expectations about Bitcoin returns. We use a model for expectations with an exponential decay of weights on past returns and find that investors extrapolate from Bitcoin’s past returns in a way that puts more weight on more recent returns. Compared to institutional investors, individuals display a higher degree of extrapolation, consistent with the perception that nonprofessionals are more prone to behavioral biases. The extrapolative component of expectations is a significant predictor of Bitcoin returns in the short term, however, its explanatory power is small. Understanding how investors in the cryptocurrency market form their beliefs is important because variation in beliefs could affect Bitcoin price dynamics and potentially lead to excess volatility, momentum, and reversal.

Capital gain overhang and risk–return trade‐off: An international study

AbstractIn this article, we examine the risk–return relation under the impact of investors' price reference points in international markets. We calculate capital gain overhang (CGO) to measure the psychological evaluation of past returns. Using a double‐sorting methodology, we find that a negative risk–return trade‐off generally exists in international markets when CGO is low; results using the Fama–MacBeth procedure confirm our findings. The CGO effect is more prominent in less developed, less transparent, and less legally protected markets. It is stronger in markets with collectivistic, higher power‐distanced, and feminine cultures. The evidence also indicates that the price reference effect is more pronounced when the market is in crisis. Finally, the CGO effect on the risk–return relation reverses as the holding period becomes longer.

The effect of prospect theory value on asset returns on the Borsa Istanbul

The goal of this study is to test the validity of the prospect theory in the Borsa Istanbul (BIST) over the sample period September 2009 to December 2019. The prospect theory values of the stocks are generated from their historical return distributions following the method by Barberis et al. (2016). Panel data analysis is implemented in six different models with market and nonmarket factors for three different data sets of stocks listed on the BIST. We employed control variables, such as Fama and French (2015) five-factor model (FF5M) factors as well as past return and skewness indicators, in the models in addition to the prospect theory value and test whether prospect theory can predict subsequent stock returns. The results show that the prospect theory value has a statistically significant effect on the asset returns and its impact is seen in particular on small-cap stocks in the Turkish stock market.

Nostalgia for utopia in the films of Theo Angelopoulos

In this article, I examine the notion of nostalgia in relation to the films of Theo Angelopoulos. I argue that the image of nostalgia that pervades his films does not call for the restoration of the past but rather lends itself to a sense of hope which I approach as an image of utopia. Drawing a line of comparison between Angelopoulos and the Greek poet George Seferis (who had a pivotal role in the shaping of a modern Greek identity and whose images of melancholy were recurrent points of reference for the director), I claim that Angelopoulos’s films are haunted by an image of utopia which is registered as a possibility in the present rather than an abstract projection into the future. Unlike Seferis’s nostalgia which is directly related to the fate of the nation, in Angelopoulos’s work the past returns to foreshadow a utopia beyond the frame of the nation state and away from the figuration of a one-way future projected by the capitalist social relations of the present.

Improving financial volatility nowcasts*

ABSTRACT Recently, a simple nowcasting model for volatility has been proposed by Breitung and Hafner [2016. A Simple Model for Now-Casting Volatility Series. International Journal of Forecasting 32 (4): 1247–1255. doi:10.1016/j.ijforecast.2016.04.007]. They suggest a model in which today's volatility is not only driven by past returns, but also by the current information from the same day. Empirical results demonstrate the relevance of the current squared return for volatility nowcasting. Their model obeys an ARMA representation estimable by maximum likelihood. However, their estimation approach builds on a number of simplifications and we suggest improvements. Rather than assuming normality of the innovations in the ARMA representation for highly skewed and leptokurtic log-squared returns, we take non-normality explicitly into account. Contrary to most situations regarding volatility estimation and forecasting, the distribution actually plays a crucial role in the construction of volatility nowcasts. We devise an exact maximum likelihood estimator which offers significant improvements in estimation efficiency and volatility nowcast accuracy in finite samples. In our empirical application, we investigate five major international stock markets from 2000 to 2019 (including sub-samples relating to the Great Financial Crisis). The results suggest that our estimation approach significantly outperforms the one by Breitung and Hafner [2016. A Simple Model for Now-Casting Volatility Series. International Journal of Forecasting 32 (4): 1247–1255. doi:10.1016/j.ijforecast.2016.04.007] in all cases. Financial volatility can be nowcasted more accurately by applying our suggested estimation approach.

Investigação da hipótese de sobrerreação e sub-reação com o sentimento do investidor

This paper aims to analyze the hypothesis of overreaction and under-reaction over the profitability of the Brazilian stock market. The theoretical review was based on the Market Efficiency and Behavioral Finance Hypothesis. Economática SA’s database was used, from where it was collected information about 1,283 stocks (571 active and 712 canceled) between January 1999 to December 2017, representing a sample of 228 months. It was applied the methodology developed by DeBondt and Thaler (1985) and Jegadeesh and Titman (1993), where portfolios composed of the upper and lower quintiles were created, based on the ranking of past stock returns. Through the means comparison test, it was possible to verify evidence that there is a phenomenon of overreaction for events of negative character after 6, 12 or 18 months of holding. However, no abnormal return was observed for overreaction of positive character events, nor any sub-reaction phenomena. Regarding investor sentiment, the results show that there is a relationship between it and the return of some strategies based on past return, contrary to Efficiency Market Hypothesis in its weak form.